News for

Set #1 solutions posted.

The audio/video time warp issue is resolved, so I finally have a video that talks about Jupyter to PDF conversion via markdown (MD) using the Typora editor. I also walk through the use of Plotly for plots versus matplotlib, and some tweaks to Typora (tweaked theme CSS file).

Lecture 3 video now posted.

Setting up a new Python 3.7x virtual environment.

3D audio simulator using pyaudio_helper. Link to GitHub in the paper. Real-time DSP in the Jupyter notebook using pyaudio_helper as presented at Scipy2018.

The use of Python >=3.7x and the Python package scikit-dsp-comm is part of this course. See the Scipy2017 tutorial instructions and information in the syllabus (updated for Python 3.7x).

Python via Pylab in the Jupyter Notebook, and now the Jupyter Lab, will be the mainstay computing platform (see also my 2015 Scipy paper).

The 'Other Course Materials' link opens up a directory listing.

Office Hours

T 3:05 to 4:15 PM and 7:05 to 8:00 PM,
or by appointment.
Phone 255-3500,

Learning Python

Python Basics a tutorial written in Jupyter Notebook. ZIP.

Link to Anaconda. This is the scientific Python I recommend.

An IDE I recommend is Pycharm Community Edition.

NumPy2MATLAB and IPython reference card

Jupyter Lab is ready. Also see, Getting started with JupyterLab (Scipy2018).

EAS RATS and LATS Servers

Obtaining Mathematica

Mathematica is available across the campus due to the CU system wide site license. This system-site license also means that students may install their own copy on home computers as well. Some links of interest regarding the CU site license for Mathematica are: download and installation and support information.

Catalog Course Description

Study of linear discrete-time systems, linear difference equations, Z-transforms, discrete Fourier transform, fast Fourier transform, sensitivity discrete random processes, quantization effects and design-related concepts.
Prerequisite: ECE 3205 and ECE 3610, or equivalent
Offered: Fall (S)

Course Materials - Course Notes, m-Code

Course Syllabus as of 09:45 PM on Wednesday, August 28, 2019.

Intro Lecture as of 10:37 PM on Sunday, August 25, 2019.

Lecture Notes

  • PDF file of Chapter 2 as of 09:27 PM on Sunday, August 25, 2019.
  • PDF file of Chapter 3 as of 09:27 PM on Sunday, August 25, 2019.
  • PDF file of Chapter 4 as of 09:27 PM on Sunday, August 25, 2019.
  • PDF file of Chapter 5 as of 09:27 PM on Sunday, August 25, 2019.
  • PDF file of Chapter 6 as of 09:27 PM on Sunday, August 25, 2019.
  • PDF file of Chapter 7 as of 09:27 PM on Sunday, August 25, 2019.
  • PDF file of Chapter 8 as of 09:27 PM on Sunday, August 25, 2019.
  • PDF file of Chapter 9 as of 03:54 PM on Saturday, March 03, 2018.

Other Course Materials

The DSP demo applications that I have used in class demos, are posted as ZIP files under the link Other Course Materials.

Support Materials for Sampling Theory

Lecture Videos - Streaming and Download

Fall 2019 Lectures as MP4 Movies

All video content is now MP4. The typical file size per lecture is about 300 MB, or less with the MP4. You may be able to stream them, but it is better to download and play from your file system.

Two videos for each lecture will be maintained. Presently [2017 to 2018], which will be replaced as new lectures occur to [2018 to 2019]. Green denotes a new 2019 lecture video.

To directly download the lectures for playback at a later time, go to the lectures folder, right click, and download

Problem Sets with Solutions
  • Set 1 as of 09:37 PM on Monday, September 09, 2019. New due date, tentative Friday September 13. IPYNB Helper Notebook. Hints as of 10:59 PM on Monday, August 26, 2019. Solved as of 10:14 PM on Monday, September 16, 2019.
  • Set 2 as of 09:48 PM on Monday, September 09, 2019.
Jupyter Example/Tutorial Notebooks

A Collection of Jupyter Notebooks

Check the posting date for the newest.

Python Projects

Python-based projects making use of Numpy and Scipy has replaced the older MATLAB projects since Fall 2014:

New Python Projects

  • Set #1p as of 03:56 PM on Thursday, November 08, 2018 and the project ZIP file as of 10:26 PM on Wednesday, November 07, 2018. The ZIP includes a sample IPYNB file for problems 1-4 and a separate notebook for problem 5.
  • Set #2p (Final Project) as of 09:54 PM on Sunday, November 25, 2018 and the project ZIP file as of 09:44 PM on Sunday, November 25, 2018. The ZIP includes a sample IPYNB file for all three problems, including quite a few code snips to get you started coding algorithms and making plots. I'm trying to streamline your efforts.
  • 2017 Final Project: Project2/Final Project as of 07:35 AM on Wednesday, December 06, 2017 and the project Project ZIP including a sample IPYNB and file as of 02:11 PM on Wednesday, November 29, 2017. Expect some updates to the sample notebook, but this will serve as a starting point.
Sample Exams with Solutions
  • TBD.

Spring Related 2020 (cont.)

A course of related interest Spring 2020 is Real-Time DSP, ECE 5655/4655-3, a three credit course on programming the ARM M4 Cortex. Keil MDK is the IDE and we make use of the ARM CMSIS-DSP library.